omega preparatory material
DESCRIPTION
OperationsTRANSCRIPT
Knowledge Material for 2015-17 Batch
Bipin| Deepak | Kishan| Ipsita | Pratik
https://www.facebook.com/Omega.IIMK
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Table of contents
About Omega……………………………………………….…………………………………………………. 03
Let’s Get Started.................................................................................................................................... 05
Responsibilities Of OM....................................................................................................................... 08
Process Performance Metrics......................................................................................................... 09
Operations Strategy............................................................................................................................. 10
7 Quality Control Tools……………………………………………………………………………….…….12
Key Reference Books……………………………………………………….……………………………….20
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Overview
This study material focuses mainly on giving you the key and basic concepts in the field of
Operations Management and to introduce the very own Operations Interest Group in God’s
Own Kampus- Omega.
What is Omega?
Before we kick off with the tutorial material, we would like to inform you briefly what is
Omega and what does Omega do as an Interest Group in IIM K.
Management is ‘The art of getting things done’. Well, someone got the definition of
Management wrong. Every activity undertaken by an organisation is to either increase its
top line or bottom line or both. How to get is done is what Operations is all about. Hence
Operations redefines management. From process improvements using Six Sigma to supply
chain management, from throughput rate to route-to-market, from aggregate planning to
inventory management, Operations encompasses it all. In the vast ocean of knowledge, we
may know very little about Operations as a business function.
Omega, the Operations Interest Group of IIM Kozhikode was founded in 2003-04 aims to
keep track of the latest in the field of Operations Management. It is a forum for Operations
Enthusiast to exchange ideas, debate about challenges and emerge with innovate solutions.
Omega focuses on providing a cutting edge to students by giving them a platform to engage
with industry experts through guest lectures, working with companies through live
projects and sharpening their skills through competitions. We have a few ideas that we
would like to share. We want to hear a lot more from you.
We have our coordinators and members who will support you during your summer
placements, guide you in competitions and conduct special sessions as and when required.
Some of our activity highlights are :
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KPMG Six Sigma Green Belt Program: A 3 day classroom training cum
certification programme on Lean Six Sigma
Operations Simulation Workshop: An opportunity for the operations enthusiasts to
gain knowledge and experience before joining the industry.
Omega Championship: A 3-round competition for identifying champions among the
brightest operation minds.
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• Management-Engineering Collaboration Initiative: An event organized in
association with Mechanical Engineering Association (MEA) at NIT Calicut for
knowledge sharing and talent upbringing among the graduates.
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Sessions by industry experts for giving their insights on topics like Project
Management, emerging technologies in SCM etc and their application in industry
Assistance to students in summer and final placements by providing preparatory
material which is a compendium of all necessary and relevant concepts in operations.
Career help for people interested in Operations Management •
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Trivia quizzes in the field of Operations Management
Information session on APICS (CSCP & CPIM)/PMI/Six Sigma Certifications
Assistance to IIC in the organization of the flagship annual event “Horizons” in the field of
Operations Management
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Developing and Conducting themes for paper writing for Backwaters
Managing the SCOPE (Supply Chain Consultants at IIMK) program, in which industry research
is done.
• Ops facebook page : We maintain an active Facebook page which has a large member base
where in we discuss trends and development in the field of Operations Management.
https://www.facebook.com/Omega.IIMK
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Let’s get started!!
OM – Operations Management
Management of ANY activities/process that create goods and provide services
Exemplary Activities:
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Forecasting
Scheduling,
Quality management
Why to study OM ?
Cost and profit breakdown at a typical manufacturing company shows that 20% cost comes
from Operations Management
How to make more profit?
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Cost cutting.
Which costs affect the revenue?
Management of operations is critical to create and maintain competitive advantages
Operations management: The management of the efficient transformation of inputs into
outputs to effectively satisfy customers.
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The active role of operations:
Inputs become Outputs after some Transformation (Process or Operation)
Food processing example:
Inputs Transformation Outputs
Energy, Raw vegetables Cleaning Clean vegetables
Energy, Metal sheets
Energy, Vegetables
Cutting/Rolling/Welding
Cutting/Chopping
Cooking
Cans
Cut vegetables
Boiled vegetables Energy, Water, Vegetables
Energy, Cans, Boiled vegetables Placing Can food
Manufacturing vs Service Operations
Production of goods
Tangible products
• Automobiles, Refrigerators, Aircrafts, Coats, Books, Sodas
Services
Repairs, Improvements, Transportation, Regulation
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Regulatory bodies: Government, Judicial system, FAA, FDA
Entertainment services: Theaters, Sport activities
Exchange services: Wholesale/retail
Appraisal services: Valuation, House appraisal
Security services: Police force, Army
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Financial services: Banks
Education: Universities, K-12 schools
Manufacturing vs Service Operations
Characteristic
Output
Manufacturing
Tangible
Low
Service
Intangible
High Customer contact
Uniformity of output
Labor content
High Low
Low High
Uniformity of input High Low
Measurement of productivity
Opportunity to correct quality problems
Easy Difficult
Difficult Easy
Manufacturing and service operations are different with respect to:
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Customer contact
Uniformity of input
Labor content of jobs
Uniformity of output
Measurement of productivity
Production and delivery
Quality assurance
Amount of Inventory
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Responsibilities of OM
Location
Capacity Degree Of
Make or Buy
Layout
Inventory
Overtime Use Quality
Costs
Subcontracting
Incentive
Plan Projects
Process
Selection Scheduling
Forecasting
In a nutshell – “Matching Supply with Demand “
Supply Side Demand Side
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Process Performance Metrics
It is of utmost importance to analyze whether a process is functioning properly or not.
Analysis requires –Measurement of Performance
Process performance metrics – measurement of different process characteristics that tell
us how a process is performing.
Measuring Productivity
It is very essential to measure the productivity as it is the key to understand the actual
performance and would also help us in identifying where to focus upon and where to
improve.
Productivity is a measure of how efficiently inputs are converted to outputs
Productivity = output/input
Total Productivity Measure
Total Productivity = $sales/inputs
Multifactor Productivity Measure
Multi-factor Productivity = sales/total costs
Measurement of Partial productivity refers to measurement solutions which do not meet
requirements of total productivity measurement, yet being practicable as indicators of total
productivity.
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Process Performance Metrics
Operations Strategy
OM Strategy is assessing and formulating the long term operations capabilities of a company and
making it aligned to the overall strategy of the organization
Customer Value can be added through:
Reducing Cost
Faster Service
Making the product readily available
Making more information available to customers
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Components of Operations Strategy
Quality
Management Reliability &
Maintenance Procurement
Planning &
Scheduling
Product &
Process Operations Strategy &
Mission
Inventory
Management Lay Out Location
Overview of Operations Management
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7 Quality Control Tools
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Pareto Analysis
Flow Chart
Scatter Diagrams
SPC Chart
Cause-and-Effect Diagram
Check Sheet
Histogram
Pareto Analysis
• Pareto analysis is a statistical technique in decision making that is used for selection of
a limited number of tasks that produce significant overall effect. It uses the Pareto
principle – the idea that by doing 20% of work, 80% of the advantage of doing the
entire job can be generated. Or in terms of quality improvement, a large majority of
problems (80%) are produced by a few key causes (20%).
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Pareto analysis is a formal technique useful where many possible courses of action
are competing for attention. In essence, the problem-solver estimates the benefit
delivered by each action, then selects a number of the most effective actions that
deliver a total benefit reasonably close to the maximal possible one.
Pareto analysis is a creative way of looking at causes of problems because it helps
stimulate thinking and organize thoughts. However, it can be limited by its exclusion
of possibly important problems which may be small initially, but which grow with
time. It should be combined with other analytical tools such as failure mode and
effects analysis and fault tree analysis for example.
• This technique helps to identify the top portion of causes that need to be addressed
to resolve the majority of problems. Once the predominant causes are identified,
then tools like the Ishikawa diagram or Fish-bone Analysis can be used to identify the
root causes of the problems. While it is common to refer to pareto as "20/80", under
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the assumption that, in all situations, 20% of causes determine 80% of problems,
this ratio is merely a convenient rule of thumb and is not nor should it be
considered immutable law of nature.
• The application of the Pareto analysis in risk management allows management to
focus on those risks that have the most impact on the project
Steps to identify the important causes using (20/80) Pareto analysis
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Step 1: Form an explicit table listing the causes and their frequency as a percentage.
Step 2: Arrange the rows in the decreasing order of importance of the causes (i.e.,
the most important cause first)
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Step 3: Add a cumulative percentage column to the table
Step 4: Plot with causes on x- and cumulative percentage on y-axis
Step 5: Join the above points to form a curve
Step 6: Plot (on the same graph) a bar graph with causes on x- and percent
frequency on y-axis
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Step 7: Draw line at 80% on y-axis parallel to x-axis. Then drop the line at the point
of intersection with the curve on x-axis. This point on the x-axis separates the
important causes (on the left) and trivial causes (on the right)
Step 8: Explicitly review the chart to ensure that at least 80% of the causes are
captured
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Flow Chart
A flowchart is a type of diagram that represents an algorithm or process, showing the
steps as boxes of various kinds, and their order by connecting them with arrows. This
diagrammatic representation solution to a given problem. Process operations are
represented in these boxes, and arrows; rather, they are implied by the sequencing of
operations. Flowcharts are used in analyzing, designing, documenting or managing a
process or program in various fields.
Flowcharts are used in designing and documenting complex processes or programs. Like
other types of diagrams, they help visualize what is going on and thereby help the viewer to
understand a process, and perhaps also find flaws, bottlenecks, and other less-obvious
features within it. There are many different types of flowcharts, and each type has its own
repertoire of boxes and notational conventions. The two most common types of boxes in a
flowchart are:
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A processing step, usually called activity, and denoted as a rectangular box
A decision, usually denoted as a diamond.
A flowchart is described as "cross-functional" when the page is divided into
different swimlanes describing the control of different organizational units. A symbol
appearing in a particular "lane" is within the control of that organizational unit. This
technique allows the author to locate the responsibility for performing an action or making
a decision correctly, showing the responsibility of each organizational unit for different
parts of a single process.
Flowcharts depict certain aspects of processes and they are usually complemented by other
types of diagram. For instance, Kaoru Ishikawa defined the flowchart as one of the seven
basic tools of quality control, next to the histogram, Pareto chart, check sheet, control
chart, cause-and-effect diagram, and the scatter diagram. Similarly, in UML, a standard
concept-modeling notation used in software development, the activity diagram, which is a
type of flowchart, is just one of many different diagram types.
Nassi-Shneiderman diagrams are an alternative notation for process flow.
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Eg : Packing and Shipping Process Flow Chart
Check Sheet
The check sheet is a form (document) used to collect data in real time at the location
where the data is generated. The data it captures can be quantitative or qualitative. When
the information is quantitative, the check sheet is sometimes called a tally sheet.
The check sheet is one of the so-called Seven Basic Tools of Quality Control.
The defining characteristic of a check sheet is that data are recorded by making marks
("checks") on it. A typical check sheet is divided into regions, and marks made in different
regions have different significance. Data are read by observing the location and number of
marks on the sheet.
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Histogram
In statistics, a histogram is a graphical representation of the distribution of data. It is an
estimate of the probability distribution of a continuous variable and was first introduced
by Karl Pearson. A histogram is a representation of tabulated frequencies, shown as
adjacent rectangles, erected over discrete intervals (bins), with an area equal to the
frequency of the observations in the interval. The height of a rectangle is also equal to the
frequency density of the interval, i.e., the frequency divided by the width of the interval.
The total area of the histogram is equal to the number of data. A histogram may also
be normalized displaying relative frequencies. It then shows the proportion of cases that
fall into each of several categories, with the total area equaling 1. The categories are usually
specified as consecutive, non-overlapping intervals of a variable. The categories (intervals)
must be adjacent, and often are chosen to be of the same size. The rectangles of a histogram
are drawn so that they touch each other to indicate that the original variable is continuous.
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Scatter Plot
A scatter plot or scatter graph is a type of mathematical diagram using Cartesian
coordinates to display values for two variables for a set of data.
The data is displayed as a collection of points, each having the value of one variable
determining the position on the horizontal axis and the value of the other variable
determining the position on the vertical axis. This kind of plot is also called a scatter
chart, scatter gram, scatter diagram or scatter graph.
A scatter plot is used when a variable exists that is below the control of the experimenter. If
a parameter exists that is systematically incremented and/or decremented by the other, it
is called the control parameter or independent variable and is customarily plotted along the
horizontal axis. The measured or dependent variable is customarily plotted along the
vertical axis. If no dependent variable exists, either type of variable can be plotted on either
axis and a scatter plot will illustrate only the degree of correlation (not causation) between
two variables.
A scatter plot can suggest various kinds of correlations between variables with a
certain confidence interval. For example, weight and height, weight would be on x axis and
height would be on the y axis. Correlations may be positive (rising), negative (falling), or
null (uncorrelated). If the pattern of dots slopes from lower left to upper right, it suggests a
positive correlation between the variables being studied. If the pattern of dots slopes from
upper left to lower right, it suggests a negative correlation
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Cause and Effect Diagram (Ishikawa Diagram)
Ishikawa diagrams (also called fishbone diagrams, herringbone diagrams, cause-and-
effect diagrams, or Fishikawa) are causal diagrams created by Kaoru Ishikawa (1968)
that show the causes of a specific event. Common uses of the Ishikawa diagram are product
design and quality defect prevention, to identify potential factors causing an overall effect.
Each cause or reason for imperfection is a source of variation. Causes are usually grouped
into major categories to identify these sources of variation.
The categories typically include:
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People: Anyone involved with the process
Methods: How the process is performed and the specific requirements for doing it,
such as policies, procedures, rules, regulations and laws
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Machines: Any equipment, computers, tools, etc. required to accomplish the job
Materials: Raw materials, parts, pens, paper, etc. used to produce the final product
Measurements: Data generated from the process that are used to evaluate its quality
Environment: The conditions, such as location, time, temperature, and culture in
which the process operates
Causes in the diagram are often categorized, such as to the 6 M's, described below. Cause-
and-effect diagrams can reveal key relationships among various variables, and the possible
causes provide additional insight into process behavior.
Causes can be derived from brainstorming sessions. These groups can then be labeled as
categories of the fishbone. They will typically be one of the traditional categories
mentioned above but may be something unique to the application in a specific case. Causes
can be traced back to root causes with the 5 Whys technique.
Typical categories are:
The 6 Ms (used in manufacturing industry)
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Machine (technology)
Method (process)
Material (Includes Raw Material, Consumables and Information.)
Man Power (physical work)/Mind Power (brain work): Kaizens, Suggestions
Measurement (Inspection)
Milieu/Mother Nature (Environment)
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Key Reference Books
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Key concepts in Operations Management by Michel Leseure.
Operations Management : The Basics by R Les Galloway
Managers Guide to Operations Management by John Kamauff
Here are some of the best Supply Chain Management & Logistics Management books
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